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sec-bert-base

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@@ -53,8 +53,6 @@ model = AutoModel.from_pretrained("nlpaueb/sec-bert-base")
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  | Sample | Masked Token |
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  | --------------------------------------------------- | ------------ |
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  | Total net sales [MASK] 2% or $5.4 billion during 2019 compared to 2018. | decreased
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  | Model | Predictions (Probability) |
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  | --------------------------------------------------- | ------------ |
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  | **BERT-BASE-UNCASED** | increased (0.221), were (0.131), are (0.103), rose (0.075), of (0.058)
 
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  | Sample | Masked Token |
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  | --------------------------------------------------- | ------------ |
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  | Total net sales [MASK] 2% or $5.4 billion during 2019 compared to 2018. | decreased
 
 
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  | Model | Predictions (Probability) |
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  | --------------------------------------------------- | ------------ |
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  | **BERT-BASE-UNCASED** | increased (0.221), were (0.131), are (0.103), rose (0.075), of (0.058)